Advances in Molecular Imaging

Advances in Molecular Imaging

ISSN Print: 2161-6728
ISSN Online: 2161-6752
www.scirp.org/journal/ami
E-mail: ami@scirp.org
"DTI and Structural MRI Classification in Alzheimer’s Disease"
written by Lilia Mesrob, Marie Sarazin, Valerie Hahn-Barma, Leonardo Cruz de Souza, Bruno Dubois, Patrick Gallinari, Serge Kinkingnéhun,
published by Advances in Molecular Imaging, Vol.2 No.2, 2012
has been cited by the following article(s):
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[2] Deep Learning-Based Segmentation in Classification of Alzheimer's Disease
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[3] Enhanced computerised diagnosis of Alzheimer's disease from brain MRI images using a classifier merger strategy
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[4] A Survey on Classification Algorithms of Brain Images in Alzheimer's Disease Based on Feature Extraction Techniques
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[5] An Ensemble Learning Approach Based on Diffusion Tensor Imaging Measures for Alzheimer's Disease Classification
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[6] An Ensemble Learning Approach Based on Diffusion Tensor Imaging Measures for Alzheimer's Disease Classification. Electronics 2021, 10, 249
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[7] Classification of multimodal MRI images using Deep Learning: Application to the diagnosis of Alzheimer's disease.
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[8] Diffusion-weighted imaging (DWI) tractography and Alzheimer's disease
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[9] Machine Learning for the Classification of Alzheimer's Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review
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[10] Characterizing white matter connectivity in Alzheimer's disease and mild cognitive impairment: An automated fiber quantification analysis with two independent …
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[11] Denouements of machine learning and multimodal diagnostic classification of Alzheimer's disease
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[12] Multimodal MRI Based Classification and Prediction of Alzheimer's Disease Using Random Forest Ensemble
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[13] Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer's disease
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[14] Classification and early detection of dementia and cognitive decline with magnetic resonance imaging
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[15] Diferential diagnosis of alzheimer's disease based on multimodal imaging data (MRI, PIB and DTI)
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[16] Applications of NODDI for imaging in vivo white matter pathology in neurodegenerative diseases
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[17] Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI
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[18] Structural and microstructural neuroimaging for diagnosis and tracking of neurodegenerative diseases
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[19] Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Normal Controls With Subnetwork Selection and Graph Kernel Principal Component …
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[20] Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease
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[21] A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease
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[22] Classification of Alzheimer's disease, mild cognitive impairment and normal controls with subnetwork selection and graph kernel principal component analysis based …
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[23] A novel approach to brain connectivity reveals early structural changes in Alzheimer's disease
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[24] A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease.
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[25] Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature …
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[26] Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging
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[27] To appear in: Computers in Biology and Medicine
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[28] Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature …
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[29] Histogram-Based Feature Extraction from Individual Gray Matter Similarity-Matrix for Alzheimer's Disease Classification
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[30] DTI measurements for Alzheimer's classification
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[31] Recognition of Alzheimer's disease and Mild Cognitive Impairment with multimodal image-derived biomarkers and Multiple Kernel Learning
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[32] Diagnosis of Alzheimer's Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features
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[33] Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease
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[34] Predicting Alzheimer Disease Status Using High-Dimensional MRI Data Based on LASSO Constrained Generalized Linear Models
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[35] Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error
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[36] A hybrid sequential feature selection approach for the diagnosis of Alzheimer's Disease
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[37] Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's …
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[38] Frontiers for the early diagnosis of AD by means of MRI brain imaging and support vector machines
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[39] Structural MRI-based classification of alzheimer's disease
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[40] Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's …
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[41] Multimodal analysis of functional and structural disconnection in A lzheimer's disease using multiple kernel SVM
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[42] Features-based MRI brain classification with domain knowledge: application to Alzheimer's disease diagnosis
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[43] Classification des IRM par les descripteurs de contenu: application au diagnostic précoce de la maladie d'Alzheimer
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[44] Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM
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[45] Feature-ranking-based Alzheimer's disease classification from structural MRI
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[46] Analysis of sub-anatomic diffusion tensor imaging indices in white matter regions of Alzheimer with MMSE score
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[47] Diffusion Tensor Imaging retrieval for Alzheimer's disease diagnosis
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[48] Brain Tumor Analysis and Classification of Brain MR Images
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[49] Evaluation of the Length of Tracked Fibers of Korean Female Adults Brain According to Life Cycle by Fiber Tractography
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[50] Using diffusion MRI technique as a tool in the early detection of Alzheimer's Disease
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[51] Dimension Reduction and Classification for High Dimensional Complex Data.
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[52] Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer's
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